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Computer Science, Engineering and Control
Supercomputer application integral characteristics analysis for the whole queued job collection of large-scale HPS systems
D. A. Nikitenko, V. V. Voevodin, A. M. Teplov, S. A. Zhumatii, Vad. V. Voevodin, K. S. Stefanov, P. A. Shvets Research Computing Center, M.V. Lomonosov Moscow State University (Leninskie Gory 1, Moscow, 119991 Russia)
Abstract:
Efficient use and high output of any supercomputer depends on a great number of factors. The problem of controlling granted resource utilization is one of those, and becomes especially noticeable in conditions of concurrent work of many user projects. It is important to provide users with detailed information on peculiarities of their executed jobs. At the same time it is important to provide project managers with detailed information on resource utilization by project members by giving access to the detailed job analysis. Unfortunately, such information is rarely available. This gap should be eliminated with our proposed approach to supercomputer application integral characteristics analysis for the whole queued job collection of large-scale HPC systems based on system monitoring data management and study, building integral job characteristics, revealing job categories and single job run peculiarities.
Keywords:
supercomputer, efficiency, system monitoring, job categories, integral job characteristics, queued job collection, job queue, resource utilization control.
Received: 11.04.2016
Citation:
D. A. Nikitenko, V. V. Voevodin, A. M. Teplov, S. A. Zhumatii, Vad. V. Voevodin, K. S. Stefanov, P. A. Shvets, “Supercomputer application integral characteristics analysis for the whole queued job collection of large-scale HPS systems”, Vestn. YuUrGU. Ser. Vych. Matem. Inform., 5:4 (2016), 32–45
Linking options:
https://www.mathnet.ru/eng/vyurv150 https://www.mathnet.ru/eng/vyurv/v5/i4/p32
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Abstract page: | 176 | Full-text PDF : | 110 | References: | 37 |
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